Probability Crash Course VCE Maths Methods | Watch this before your first probability lesson

Описание: Start your VCE Maths Methods probability journey with confidence! This crash course covers all the essential probability concepts you need before your first lesson. We’ll walk you through sample spaces, events, probability rules (including addition and complement), conditional probability, independence, discrete random variables, binomial distributions, and how to use cumulative distribution functions (CDFs)—all explained with clear, practical examples.

This video is perfect for Year 11 and 12 students who want a solid foundation in probability without getting bogged down in the calculations for expected value, variance, or standard deviation of continuous random variables (those are in the next video!). Watch now and set yourself up for success in VCE Mathematical Methods.

0:00 - Intro: Sample Spaces and Events
3:05 - Complement Rule
4:36 - Addition Rule
6:56 - Addition Rule for Mutually Exclusive Events
8:42 - Example: Applying the Addition Rule
12:22 - Conditional Probability
17:33 - Conditional Probability for Independent Events
19:46 - Discrete vs Continuous Random Variables
21:58 - Discrete Probability Distributions and Probability Mass Functions
23:42 - Example: Discrete Random Variable
24:54 - Example 1: Finding E(X) of a Discrete Random Variable
26:08 - Example 2: Finding E(X) of a Discrete Random Variable
28:18 - Example: Binomial Distribution
33:05 - Intro to Continuous Probability Distributions
33:52 - Intro to the Normal Distribution
34:19 - Example: Calculating and Understanding the Var(X) of Discrete Random Variables
36:30 - Example: Calculating and Understanding the Std Deviation in Relation to the Normal Distribution
37:36 - Normal Distribution Cont'd: 68/95/99.7 Rule
40:32 - Understanding Standardisation of a Normal Distribution
43:00 - Example: Standardising a Normal Distribution
46:03 - Cumulative Distribution Functions for Discrete and Continuous Random Variables
48:14 - Note: See the next video to learn how to calculate E(X) and Var(X) of a Continuous Random Variable